Abstract

Light-scattering methods are widely used in soft matter physics and biomedical optics to probe dynamics in turbid media, such as diffusion in colloids or blood flow in biological tissue. These methods typically rely on fluctuations of coherent light intensity, and therefore cannot accommodate more than a few modes per detector. This limitation has hindered efforts to measure deep tissue blood flow with high speed, since weak diffuse light fluxes, together with low single-mode fiber throughput, result in low photon count rates. To solve this, we introduce multimode fiber (MMF) interferometry to the field of diffuse optics. In doing so, we transform a standard complementary metal-oxide-semiconductor (CMOS) camera into a sensitive detector array for weak light fluxes that probe deep in biological tissue. Specifically, we build a novel CMOS-based, multimode interferometric diffusing wave spectroscopy (iDWS) system and show that it can measure 20 speckles simultaneously near the shot noise limit, acting essentially as 20 independent photon-counting channels. We develop a matrix formalism, based on MMF mode field solutions and detector geometry, to predict both coherence and speckle number in iDWS. After validation in liquid phantoms, we demonstrate iDWS pulsatile blood flow measurements at 2.5 cm source-detector separation in the adult human brain in vivo. By achieving highly sensitive and parallel measurements of coherent light fluctuations with a CMOS camera, this work promises to enhance performance and reduce cost of diffuse optical instruments.

© 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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References

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2017 (5)

2016 (3)

2014 (4)

T. Durduran and A. G. Yodh, “Diffuse correlation spectroscopy for non-invasive, micro-vascular cerebral blood flow measurement,” NeuroImage 85, 51–63 (2014).
[Crossref]

E. M. Buckley, A. B. Parthasarathy, P. E. Grant, A. G. Yodh, and M. A. Franceschini, “Diffuse correlation spectroscopy for measurement of cerebral blood flow: future prospects,” Neurophotonics 1, 011009 (2014).
[Crossref]

L. Mei, G. Somesfalean, and S. Svanberg, “Frequency-modulated light scattering interferometry employed for optical properties and dynamics studies of turbid media,” Biomed. Opt. Express 5, 2810–2822 (2014).
[Crossref]

B. Redding, M. Alam, M. Seifert, and H. Cao, “High-resolution and broadband all-fiber spectrometers,” Optica 1, 175–180 (2014).
[Crossref]

2013 (5)

2012 (1)

M. Davy, Z. Shi, and A. Z. Genack, “Focusing through random media: eigenchannel participation number and intensity correlation,” Phys. Rev. B 85, 035105 (2012).
[Crossref]

2011 (1)

2010 (2)

K. Zarychta, E. Tinet, L. Azizi, S. Avrillier, D. Ettori, and J.-M. Tualle, “Time-resolved diffusing wave spectroscopy with a CCD camera,” Opt. Express 18, 16289–16301 (2010).
[Crossref]

T. Durduran, R. Choe, W. B. Baker, and A. G. Yodh, “Diffuse optics for tissue monitoring and tomography,” Rep. Prog. Phys. 73, 076701 (2010).
[Crossref]

2007 (1)

2006 (1)

2002 (1)

V. Viasnoff, F. Lequeux, and D. J. Pine, “Multispeckle diffusing-wave spectroscopy: a tool to study slow relaxation and time-dependent dynamics,” Rev. Sci. Instrum. 73, 2336–2344 (2002).
[Crossref]

2001 (1)

1998 (1)

K. K. Bizheva, A. M. Siegel, and D. A. Boas, “Path-length-resolved dynamic light scattering in highly scattering random media: the transition to diffusing wave spectroscopy,” Phys. Rev. E 58, 7664–7667 (1998).
[Crossref]

1997 (1)

1991 (2)

A. G. Yodh, N. Georgiades, and D. J. Pine, “Diffusing-wave interferometry,” Opt. Commun. 83, 56–59 (1991).
[Crossref]

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254, 1178–1181 (1991).
[Crossref]

1988 (1)

D. J. Pine, D. A. Weitz, P. M. Chaikin, and E. Herbolzheimer, “Diffusing wave spectroscopy,” Phys. Rev. Lett. 60, 1134–1137 (1988).
[Crossref]

1987 (1)

G. Maret and P. E. Wolf, “Multiple light scattering from disordered media. The effect of Brownian motion of scatterers,” Z. Phys. B 65, 409–413 (1987).
[Crossref]

Alam, M.

Argueta-Morales, R.

J. R. Guzman-Sepulveda, R. Argueta-Morales, W. M. DeCampli, and A. Dogariu, “Real-time intraoperative monitoring of blood coagulability via coherence-gated light scattering,” Nat. Biomed. Eng. 1, 0028 (2017).
[Crossref]

Avrillier, S.

Azizi, L.

Baker, W. B.

Belau, M.

Bizheva, K. K.

K. K. Bizheva, A. M. Siegel, and D. A. Boas, “Path-length-resolved dynamic light scattering in highly scattering random media: the transition to diffusing wave spectroscopy,” Phys. Rev. E 58, 7664–7667 (1998).
[Crossref]

Boas, D. A.

Borycki, D.

Buckley, E. M.

E. M. Buckley, A. B. Parthasarathy, P. E. Grant, A. G. Yodh, and M. A. Franceschini, “Diffuse correlation spectroscopy for measurement of cerebral blood flow: future prospects,” Neurophotonics 1, 011009 (2014).
[Crossref]

Busch, D. R.

Cao, H.

Carp, S. A.

Chaikin, P. M.

D. J. Pine, D. A. Weitz, P. M. Chaikin, and E. Herbolzheimer, “Diffusing wave spectroscopy,” Phys. Rev. Lett. 60, 1134–1137 (1988).
[Crossref]

Chandra, M.

Chang, W.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254, 1178–1181 (1991).
[Crossref]

Cheikh, M.

Cheng, R.

D. Irwin, L. Dong, Y. Shang, R. Cheng, M. Kudrimoti, S. D. Stevens, and G. Yu, “Influences of tissue absorption and scattering on diffuse correlation spectroscopy blood flow measurements,” Biomed. Opt. Express 2, 1969–1985 (2011).
[Crossref]

G. Yu, T. Durduran, C. Zhou, R. Cheng, and A. Yodh, “Near-infrared diffuse correlation spectroscopy for assessment of tissue blood flow,” in Handbook of Biomedical Optics (CRC Press, 2011), pp. 195–216.

Choe, R.

T. Durduran, R. Choe, W. B. Baker, and A. G. Yodh, “Diffuse optics for tissue monitoring and tomography,” Rep. Prog. Phys. 73, 076701 (2010).
[Crossref]

Dasari, R. R.

Davy, M.

M. Davy, Z. Shi, J. Wang, and A. Z. Genack, “Transmission statistics and focusing in single disordered samples,” Opt. Express 21, 10367–10375 (2013).
[Crossref]

M. Davy, Z. Shi, and A. Z. Genack, “Focusing through random media: eigenchannel participation number and intensity correlation,” Phys. Rev. B 85, 035105 (2012).
[Crossref]

DeCampli, W. M.

J. R. Guzman-Sepulveda, R. Argueta-Morales, W. M. DeCampli, and A. Dogariu, “Real-time intraoperative monitoring of blood coagulability via coherence-gated light scattering,” Nat. Biomed. Eng. 1, 0028 (2017).
[Crossref]

Detre, J. A.

Dietsche, G.

Dogariu, A.

J. R. Guzman-Sepulveda, R. Argueta-Morales, W. M. DeCampli, and A. Dogariu, “Real-time intraoperative monitoring of blood coagulability via coherence-gated light scattering,” Nat. Biomed. Eng. 1, 0028 (2017).
[Crossref]

Dong, L.

Douglas Stone, A.

C. W. Hsu, S. F. Liew, A. Goetschy, H. Cao, and A. Douglas Stone, “Correlation-enhanced control of wave focusing in disordered media,” Nat. Phys. 13, 497–502 (2017).
[Crossref]

Durduran, T.

T. Durduran and A. G. Yodh, “Diffuse correlation spectroscopy for non-invasive, micro-vascular cerebral blood flow measurement,” NeuroImage 85, 51–63 (2014).
[Crossref]

T. Durduran, R. Choe, W. B. Baker, and A. G. Yodh, “Diffuse optics for tissue monitoring and tomography,” Rep. Prog. Phys. 73, 076701 (2010).
[Crossref]

G. Yu, T. Durduran, C. Zhou, R. Cheng, and A. Yodh, “Near-infrared diffuse correlation spectroscopy for assessment of tissue blood flow,” in Handbook of Biomedical Optics (CRC Press, 2011), pp. 195–216.

Ettori, D.

Farzam, P.

Favilla, C. G.

Feld, M. S.

Flotte, T.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254, 1178–1181 (1991).
[Crossref]

Franceschini, M. A.

Friberg, A. T.

Fujimoto, J. G.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254, 1178–1181 (1991).
[Crossref]

Gannon, K.

Genack, A. Z.

M. Davy, Z. Shi, J. Wang, and A. Z. Genack, “Transmission statistics and focusing in single disordered samples,” Opt. Express 21, 10367–10375 (2013).
[Crossref]

M. Davy, Z. Shi, and A. Z. Genack, “Focusing through random media: eigenchannel participation number and intensity correlation,” Phys. Rev. B 85, 035105 (2012).
[Crossref]

Georgiades, N.

A. G. Yodh, N. Georgiades, and D. J. Pine, “Diffusing-wave interferometry,” Opt. Commun. 83, 56–59 (1991).
[Crossref]

Gisler, T.

Goetschy, A.

C. W. Hsu, S. F. Liew, A. Goetschy, H. Cao, and A. Douglas Stone, “Correlation-enhanced control of wave focusing in disordered media,” Nat. Phys. 13, 497–502 (2017).
[Crossref]

Goodman, J. W.

J. W. Goodman, “Statistical properties of laser speckle patterns,” in Laser Speckle and Related Phenomena (Springer, 1975), pp. 9–75.

Grant, P. E.

E. M. Buckley, A. B. Parthasarathy, P. E. Grant, A. G. Yodh, and M. A. Franceschini, “Diffuse correlation spectroscopy for measurement of cerebral blood flow: future prospects,” Neurophotonics 1, 011009 (2014).
[Crossref]

Greenberg, J. H.

Gregory, K.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254, 1178–1181 (1991).
[Crossref]

Gulinatti, A.

Guzman-Sepulveda, J. R.

J. R. Guzman-Sepulveda, R. Argueta-Morales, W. M. DeCampli, and A. Dogariu, “Real-time intraoperative monitoring of blood coagulability via coherence-gated light scattering,” Nat. Biomed. Eng. 1, 0028 (2017).
[Crossref]

He, L.

L. He, Y. Lin, Y. Shang, B. J. Shelton, and G. Yu, “Using optical fibers with different modes to improve the signal-to-noise ratio of diffuse correlation spectroscopy flow-oximeter measurements,” J. Biomed. Opt. 18, 037001 (2013).
[Crossref]

Hee, M. R.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254, 1178–1181 (1991).
[Crossref]

Herbolzheimer, E.

D. J. Pine, D. A. Weitz, P. M. Chaikin, and E. Herbolzheimer, “Diffusing wave spectroscopy,” Phys. Rev. Lett. 60, 1134–1137 (1988).
[Crossref]

Hsu, C. W.

C. W. Hsu, S. F. Liew, A. Goetschy, H. Cao, and A. Douglas Stone, “Correlation-enhanced control of wave focusing in disordered media,” Nat. Phys. 13, 497–502 (2017).
[Crossref]

Huang, D.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254, 1178–1181 (1991).
[Crossref]

Hueber, D. M.

Hui, C.

B. Redding, S. F. Liew, R. Sarma, and C. Hui, “Compact spectrometer based on a disordered photonic chip,” Nat. Photonics 7, 746–751 (2013).
[Crossref]

Irwin, D.

Jaillon, F.

Kavuri, V.

Kholiqov, O.

Ko, T.

Kudrimoti, M.

Lequeux, F.

V. Viasnoff, F. Lequeux, and D. J. Pine, “Multispeckle diffusing-wave spectroscopy: a tool to study slow relaxation and time-dependent dynamics,” Rev. Sci. Instrum. 73, 2336–2344 (2002).
[Crossref]

Li, J.

Li, Z.

Liew, S. F.

C. W. Hsu, S. F. Liew, A. Goetschy, H. Cao, and A. Douglas Stone, “Correlation-enhanced control of wave focusing in disordered media,” Nat. Phys. 13, 497–502 (2017).
[Crossref]

B. Redding, S. F. Liew, R. Sarma, and C. Hui, “Compact spectrometer based on a disordered photonic chip,” Nat. Photonics 7, 746–751 (2013).
[Crossref]

Lin, C. P.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254, 1178–1181 (1991).
[Crossref]

Lin, Y.

L. He, Y. Lin, Y. Shang, B. J. Shelton, and G. Yu, “Using optical fibers with different modes to improve the signal-to-noise ratio of diffuse correlation spectroscopy flow-oximeter measurements,” J. Biomed. Opt. 18, 037001 (2013).
[Crossref]

Lu, X.

Maret, G.

M. Belau, W. Scheffer, and G. Maret, “Pulse wave analysis with diffusing-wave spectroscopy,” Biomed. Opt. Express 8, 3493–3500 (2017).
[Crossref]

G. Maret and P. E. Wolf, “Multiple light scattering from disordered media. The effect of Brownian motion of scatterers,” Z. Phys. B 65, 409–413 (1987).
[Crossref]

Mei, L.

Mesquita, R. C.

Minkoff, D. L.

Mullen, M. T.

Nghiêm, H. L.

Ninck, M.

Ortolf, C.

Parthasarathy, A. B.

D. Wang, A. B. Parthasarathy, W. B. Baker, K. Gannon, V. Kavuri, T. Ko, S. Schenkel, Z. Li, Z. Li, M. T. Mullen, J. A. Detre, and A. G. Yodh, “Fast blood flow monitoring in deep tissues with real-time software correlators,” Biomed. Opt. Express 7, 776–797 (2016).
[Crossref]

E. M. Buckley, A. B. Parthasarathy, P. E. Grant, A. G. Yodh, and M. A. Franceschini, “Diffuse correlation spectroscopy for measurement of cerebral blood flow: future prospects,” Neurophotonics 1, 011009 (2014).
[Crossref]

Pine, D. J.

V. Viasnoff, F. Lequeux, and D. J. Pine, “Multispeckle diffusing-wave spectroscopy: a tool to study slow relaxation and time-dependent dynamics,” Rev. Sci. Instrum. 73, 2336–2344 (2002).
[Crossref]

A. G. Yodh, N. Georgiades, and D. J. Pine, “Diffusing-wave interferometry,” Opt. Commun. 83, 56–59 (1991).
[Crossref]

D. J. Pine, D. A. Weitz, P. M. Chaikin, and E. Herbolzheimer, “Diffusing wave spectroscopy,” Phys. Rev. Lett. 60, 1134–1137 (1988).
[Crossref]

Popoff, S. M.

Puliafito, C. A.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254, 1178–1181 (1991).
[Crossref]

Rech, I.

Redding, B.

Redes, N.

Saleh, B. E. A.

M. C. Teich and B. E. A. Saleh, “Noise in photodetectors,” in Fundamentals of Photonics (Wiley-Interscience, 1991), pp. 673–691.

Sarma, R.

B. Redding, S. F. Liew, R. Sarma, and C. Hui, “Compact spectrometer based on a disordered photonic chip,” Nat. Photonics 7, 746–751 (2013).
[Crossref]

Scheffer, W.

Schenkel, S.

Schenkel, S. S.

Schuman, J. S.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254, 1178–1181 (1991).
[Crossref]

Seifert, M.

Selb, J.

Setälä, T.

Shang, Y.

L. He, Y. Lin, Y. Shang, B. J. Shelton, and G. Yu, “Using optical fibers with different modes to improve the signal-to-noise ratio of diffuse correlation spectroscopy flow-oximeter measurements,” J. Biomed. Opt. 18, 037001 (2013).
[Crossref]

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[Crossref]

Shelton, B. J.

L. He, Y. Lin, Y. Shang, B. J. Shelton, and G. Yu, “Using optical fibers with different modes to improve the signal-to-noise ratio of diffuse correlation spectroscopy flow-oximeter measurements,” J. Biomed. Opt. 18, 037001 (2013).
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[Crossref]

M. Davy, Z. Shi, and A. Z. Genack, “Focusing through random media: eigenchannel participation number and intensity correlation,” Phys. Rev. B 85, 035105 (2012).
[Crossref]

Siegel, A. M.

K. K. Bizheva, A. M. Siegel, and D. A. Boas, “Path-length-resolved dynamic light scattering in highly scattering random media: the transition to diffusing wave spectroscopy,” Phys. Rev. E 58, 7664–7667 (1998).
[Crossref]

Somesfalean, G.

Srinivasan, V. J.

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Stinson, W. G.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254, 1178–1181 (1991).
[Crossref]

Sutin, J.

Svanberg, S.

Swanson, E. A.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254, 1178–1181 (1991).
[Crossref]

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Teich, M. C.

M. C. Teich and B. E. A. Saleh, “Noise in photodetectors,” in Fundamentals of Photonics (Wiley-Interscience, 1991), pp. 673–691.

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V. Viasnoff, F. Lequeux, and D. J. Pine, “Multispeckle diffusing-wave spectroscopy: a tool to study slow relaxation and time-dependent dynamics,” Rev. Sci. Instrum. 73, 2336–2344 (2002).
[Crossref]

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Yang, C.

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A. Yariv and P. Yeh, “Elementary theory of coherence,” in Photonics: Optical Electronics in Modern Communications (Oxford University, 2007), pp. 56–59.

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A. Yariv and P. Yeh, “Elementary theory of coherence,” in Photonics: Optical Electronics in Modern Communications (Oxford University, 2007), pp. 56–59.

Yodh, A.

G. Yu, T. Durduran, C. Zhou, R. Cheng, and A. Yodh, “Near-infrared diffuse correlation spectroscopy for assessment of tissue blood flow,” in Handbook of Biomedical Optics (CRC Press, 2011), pp. 195–216.

Yodh, A. G.

D. Wang, A. B. Parthasarathy, W. B. Baker, K. Gannon, V. Kavuri, T. Ko, S. Schenkel, Z. Li, Z. Li, M. T. Mullen, J. A. Detre, and A. G. Yodh, “Fast blood flow monitoring in deep tissues with real-time software correlators,” Biomed. Opt. Express 7, 776–797 (2016).
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T. Durduran and A. G. Yodh, “Diffuse correlation spectroscopy for non-invasive, micro-vascular cerebral blood flow measurement,” NeuroImage 85, 51–63 (2014).
[Crossref]

E. M. Buckley, A. B. Parthasarathy, P. E. Grant, A. G. Yodh, and M. A. Franceschini, “Diffuse correlation spectroscopy for measurement of cerebral blood flow: future prospects,” Neurophotonics 1, 011009 (2014).
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T. Durduran, R. Choe, W. B. Baker, and A. G. Yodh, “Diffuse optics for tissue monitoring and tomography,” Rep. Prog. Phys. 73, 076701 (2010).
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[Crossref]

A. G. Yodh, N. Georgiades, and D. J. Pine, “Diffusing-wave interferometry,” Opt. Commun. 83, 56–59 (1991).
[Crossref]

Yu, G.

L. He, Y. Lin, Y. Shang, B. J. Shelton, and G. Yu, “Using optical fibers with different modes to improve the signal-to-noise ratio of diffuse correlation spectroscopy flow-oximeter measurements,” J. Biomed. Opt. 18, 037001 (2013).
[Crossref]

D. Irwin, L. Dong, Y. Shang, R. Cheng, M. Kudrimoti, S. D. Stevens, and G. Yu, “Influences of tissue absorption and scattering on diffuse correlation spectroscopy blood flow measurements,” Biomed. Opt. Express 2, 1969–1985 (2011).
[Crossref]

G. Yu, T. Durduran, C. Zhou, R. Cheng, and A. Yodh, “Near-infrared diffuse correlation spectroscopy for assessment of tissue blood flow,” in Handbook of Biomedical Optics (CRC Press, 2011), pp. 195–216.

Zarychta, K.

Zhou, C.

G. Yu, T. Durduran, C. Zhou, R. Cheng, and A. Yodh, “Near-infrared diffuse correlation spectroscopy for assessment of tissue blood flow,” in Handbook of Biomedical Optics (CRC Press, 2011), pp. 195–216.

Zimmerman, B.

Appl. Opt. (2)

Biomed. Opt. Express (6)

M. Belau, W. Scheffer, and G. Maret, “Pulse wave analysis with diffusing-wave spectroscopy,” Biomed. Opt. Express 8, 3493–3500 (2017).
[Crossref]

D. Irwin, L. Dong, Y. Shang, R. Cheng, M. Kudrimoti, S. D. Stevens, and G. Yu, “Influences of tissue absorption and scattering on diffuse correlation spectroscopy blood flow measurements,” Biomed. Opt. Express 2, 1969–1985 (2011).
[Crossref]

S. A. Carp, P. Farzam, N. Redes, D. M. Hueber, and M. A. Franceschini, “Combined multi-distance frequency domain and diffuse correlation spectroscopy system with simultaneous data acquisition and real-time analysis,” Biomed. Opt. Express 8, 3993–4006 (2017).
[Crossref]

D. Wang, A. B. Parthasarathy, W. B. Baker, K. Gannon, V. Kavuri, T. Ko, S. Schenkel, Z. Li, Z. Li, M. T. Mullen, J. A. Detre, and A. G. Yodh, “Fast blood flow monitoring in deep tissues with real-time software correlators,” Biomed. Opt. Express 7, 776–797 (2016).
[Crossref]

R. C. Mesquita, S. S. Schenkel, D. L. Minkoff, X. Lu, C. G. Favilla, P. M. Vora, D. R. Busch, M. Chandra, J. H. Greenberg, J. A. Detre, and A. G. Yodh, “Influence of probe pressure on the diffuse correlation spectroscopy blood flow signal: extra-cerebral contributions,” Biomed. Opt. Express 4, 978–994 (2013).
[Crossref]

L. Mei, G. Somesfalean, and S. Svanberg, “Frequency-modulated light scattering interferometry employed for optical properties and dynamics studies of turbid media,” Biomed. Opt. Express 5, 2810–2822 (2014).
[Crossref]

J. Biomed. Opt. (1)

L. He, Y. Lin, Y. Shang, B. J. Shelton, and G. Yu, “Using optical fibers with different modes to improve the signal-to-noise ratio of diffuse correlation spectroscopy flow-oximeter measurements,” J. Biomed. Opt. 18, 037001 (2013).
[Crossref]

J. Opt. Soc. Am. A (3)

Nat. Biomed. Eng. (1)

J. R. Guzman-Sepulveda, R. Argueta-Morales, W. M. DeCampli, and A. Dogariu, “Real-time intraoperative monitoring of blood coagulability via coherence-gated light scattering,” Nat. Biomed. Eng. 1, 0028 (2017).
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Nat. Photonics (1)

B. Redding, S. F. Liew, R. Sarma, and C. Hui, “Compact spectrometer based on a disordered photonic chip,” Nat. Photonics 7, 746–751 (2013).
[Crossref]

Nat. Phys. (1)

C. W. Hsu, S. F. Liew, A. Goetschy, H. Cao, and A. Douglas Stone, “Correlation-enhanced control of wave focusing in disordered media,” Nat. Phys. 13, 497–502 (2017).
[Crossref]

NeuroImage (1)

T. Durduran and A. G. Yodh, “Diffuse correlation spectroscopy for non-invasive, micro-vascular cerebral blood flow measurement,” NeuroImage 85, 51–63 (2014).
[Crossref]

Neurophotonics (1)

E. M. Buckley, A. B. Parthasarathy, P. E. Grant, A. G. Yodh, and M. A. Franceschini, “Diffuse correlation spectroscopy for measurement of cerebral blood flow: future prospects,” Neurophotonics 1, 011009 (2014).
[Crossref]

Opt. Commun. (1)

A. G. Yodh, N. Georgiades, and D. J. Pine, “Diffusing-wave interferometry,” Opt. Commun. 83, 56–59 (1991).
[Crossref]

Opt. Express (3)

Opt. Lett. (1)

Optica (2)

Phys. Rev. B (1)

M. Davy, Z. Shi, and A. Z. Genack, “Focusing through random media: eigenchannel participation number and intensity correlation,” Phys. Rev. B 85, 035105 (2012).
[Crossref]

Phys. Rev. E (1)

K. K. Bizheva, A. M. Siegel, and D. A. Boas, “Path-length-resolved dynamic light scattering in highly scattering random media: the transition to diffusing wave spectroscopy,” Phys. Rev. E 58, 7664–7667 (1998).
[Crossref]

Phys. Rev. Lett. (1)

D. J. Pine, D. A. Weitz, P. M. Chaikin, and E. Herbolzheimer, “Diffusing wave spectroscopy,” Phys. Rev. Lett. 60, 1134–1137 (1988).
[Crossref]

Rep. Prog. Phys. (1)

T. Durduran, R. Choe, W. B. Baker, and A. G. Yodh, “Diffuse optics for tissue monitoring and tomography,” Rep. Prog. Phys. 73, 076701 (2010).
[Crossref]

Rev. Sci. Instrum. (1)

V. Viasnoff, F. Lequeux, and D. J. Pine, “Multispeckle diffusing-wave spectroscopy: a tool to study slow relaxation and time-dependent dynamics,” Rev. Sci. Instrum. 73, 2336–2344 (2002).
[Crossref]

Science (1)

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254, 1178–1181 (1991).
[Crossref]

Z. Phys. B (1)

G. Maret and P. E. Wolf, “Multiple light scattering from disordered media. The effect of Brownian motion of scatterers,” Z. Phys. B 65, 409–413 (1987).
[Crossref]

Other (5)

G. Yu, T. Durduran, C. Zhou, R. Cheng, and A. Yodh, “Near-infrared diffuse correlation spectroscopy for assessment of tissue blood flow,” in Handbook of Biomedical Optics (CRC Press, 2011), pp. 195–216.

A. Yariv and P. Yeh, “Elementary theory of coherence,” in Photonics: Optical Electronics in Modern Communications (Oxford University, 2007), pp. 56–59.

J. W. Goodman, “Statistical properties of laser speckle patterns,” in Laser Speckle and Related Phenomena (Springer, 1975), pp. 9–75.

M. C. Teich and B. E. A. Saleh, “Noise in photodetectors,” in Fundamentals of Photonics (Wiley-Interscience, 1991), pp. 673–691.

Due to the in-phase measurement, singular values are determined from svd([Re{T}, Im{T}]) instead of svd(T), the more common expression for a complex random matrix. It can be shown that SANRs determined from both singular value decomposition (svd) methods are equivalent. However, while speckle numbers determined from both svd methods agree well for the MMITMs investigated in this study, the methods are not interchangeable.

Supplementary Material (2)

NameDescription
» Supplement 1       Supplemental document.
» Visualization 1       Simulated 1-D dynamic multimode interference patterns and corresponding heterodyne signals of multimode iDWS, with and without additive noise.

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Figures (7)

Fig. 1.
Fig. 1. MMF interference pattern between ES and ER, formed by core modes with equal magnitudes and random phases. The vector electric field possesses two orthogonal transverse (x and y) components (top row). The resulting speckle pattern comprises a sample, reference, and heterodyne term (bottom row). In this example, sample and reference speckle patterns have equal power, maximizing the contrast of the heterodyne interference term (bottom right, purple text).
Fig. 2.
Fig. 2. (a) Schematic of multimode iDWS system based on an M-Z interferometer built from two fiber couplers. The first SMF-28 fiber coupler supports the first six vectorial modes (HE11×2, TE01, HE21×2, and TM01) at 852 nm. In the reference arm, the SMF-28 output fiber connects to the MMF coupler via an APC mating sleeve, with a variable attenuator to avoid camera saturation. The splitting ratio of the MMF coupler is 95/5 (T/R). The core and cladding diameters of the step-index MMF are 105 μm and 125 μm, respectively, and the NA is 0.15. The light source is an 852 nm DBR (distributed Bragg reflector) laser with <1  MHz linewidth and >180  mW output power, modulated by a 500 mA LC (laser controller, D2-105-500, Vescent Photonics) with a PS (power supply, D2-005, Vescent Photonics). L1 and L2: spherical lens; CL1 and CL2: cylindrical lens; PC: personal computer. (b) The intensity pattern at the MMF coupler output is detected by a 512 pixel CMOS array. Pixels are binned horizontally to form NPixel binned pixels consisting of 512/NPixel pixels each, with fractional heights of aSlit. (c) Instantaneous power measured by the pixel array with NPixel=512 and aSlit=1. (d) Segments of heterodyne signal time courses (1  ms) extracted from the three pixels marked by vertical dashed lines in (c). (e) Normalized field autocorrelations calculated from full-time courses (100  ms) of the three heterodyne signals in (d).
Fig. 3.
Fig. 3. Optimization of horizontal pixel binning. (a) Simulated g1(τd) for NPixel ranging from 512 to 1 with aSlit=1 and NMode=1702, where total sample and reference photon numbers detected by the 512 camera pixels are set as 41 and 4.1×106 per 3 μs exposure, respectively. (b) RMSE of decay rates versus NPixel for NMode of 1702, 1300, 900, and 500, estimated from 20 independent sets of simulations each. (c) SANR versus NPixel estimated from simulations with digitization (open symbols) and calculated from the corresponding MMITMs (solid lines). (d) Speckle number versus NPixel estimated from simulations with digitization (open symbols) and calculated from the corresponding MMITMs (solid lines). Red dashed curves in (c) and (d) indicate theoretical SANR for binning of fully correlated pixels and theoretical speckle number for binning of uncorrelated pixels, respectively. The optimal NPixel of 64 is indicated by vertical dotted lines in (b), (c), and (d).
Fig. 4.
Fig. 4. Tradeoff between coherence and pixel photon number incurred by binning. Distributions of instantaneous, local MCD values, γSR [Eq. (8) without time- or sensor-element-averaging], across pixels for different amounts of binning (NPixel), with aSlit=1 and 1702 random sample modes interfering with a fixed reference MMF pattern of either 1702 (a) or 500 (b) modes. (c) N¯S and simulated γ¯SR versus NPixel based on 400 random sample MMF patterns, with different NMode (open symbols). (d) SANRs calculated based on Eq. (10) from γ¯SR and N¯S shown in (c) (open symbols). Corresponding SANRs calculated from MMITMs are shown as solid lines in (c) and (d) for comparison.
Fig. 5.
Fig. 5. Optimization of fractional vertical slit height. (a) Simulated g1(τd) for different aSlit with NPixel=64 and NMode=1702, where total sample and reference photon numbers detected by the 512 camera pixels are set as 41 and 4.1×106 per 3 μs exposure for aSlit=1, respectively. (b) RMSE of decay rates versus aSlit for NMode of 1702, 1300, 900, and 500, estimated from 20 independent sets of simulations each. (c) SANR versus aSlit estimated from simulations with digitization (open symbols) and calculated from the corresponding MMITMs (solid lines). (d) Speckle number versus aSlit estimated from simulations with digitization (open symbols) and calculated from the corresponding MMITMs (solid lines). Vertical dotted lines in (b), (c), and (d) mark an aSlit threshold of 0.2, above which minimal changes in SANR and speckle number are observed.
Fig. 6.
Fig. 6. Tradeoff between coherence and pixel photon number incurred by changing slit height. Distributions of instantaneous, local MCD values, γSR, across pixels for different aSlit, with NPixel=64 and 1702 random sample modes interfering with a fixed reference MMF pattern of either 1702 (a) or 500 (b) modes. (c) N¯S and simulated γ¯SR versus aSlit based on 400 random sample MMF patterns, with different numbers of reference modes NMode (open symbols). (d) SANRs calculated based on Eq. (10) from γ¯SR and N¯S shown in (c) (open symbols). Corresponding SANRs calculated from MMITMs are shown as solid lines in (c) and (d) for comparison.
Fig. 7.
Fig. 7. Multimode iDWS in experimental phantoms and in vivo. (a) Normalized field autocorrelations, g1(τd,ρ), of an Intralipid phantom at different S-D separations (symbols). Corresponding exponential fits are indicated by solid lines. (b) Diffusion coefficient (DB) values estimated by fitting G1(τd,ρ) are independent of ρ. Error bars indicate 95% confidence intervals of DB estimates. (c) Evolution of g1(τd) from 7°C to 19°C at an S-D separation of 2.5 cm. The decay time of g1(τd), τc, is indicated by black line. (d) Temperature-dependent diffusion coefficients, DB, were estimated by fitting G1(τd) in two independent experiments. Shaded regions indicate 95% confidence intervals of DB estimates. The black line is the fit of the Einstein–Stokes equation. (e) In vivo pulsatile blood flow index (BFI) measured from the human brain with a 2.5 cm S-D separation. Shaded regions indicate 95% confidence intervals of BFI estimates. The left inset of panel 7(e) shows the FFT spectrum of the BFI fluctuations, where a heart rate of 1.2  Hz is evident. The right inset shows field autocorrelations, g1(τd), averaged over four systolic maxima (red) and four diastolic minima (blue), respectively, with corresponding fits. Integration times tint for estimating G1(τd) are 1 s and 0.1 s for the phantom and in vivo experiments, respectively. NPixel is 64 for all experiments.

Equations (12)

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I=|ES+ER|2=|ES|2+|ER|2+2Re{ES*·ER},
ES(x,y)=maS,mΨm(x,y)exp[i(ωtβmLS)],
ER(x,y)=naR,nΨn(x,y)exp[i(ωtβnLR)],
Pp=p|mAS,mΨm(x,y)+nAR,nΨn(x,y)|2dxdy=p[|mAS,mΨm(x,y)|2+|nAR,nΨn(x,y)|2+2Re{mnAS,m*Ψm*(x,y)·AR,nΨn(x,y)}]dxdy=PS,p+PR,p+PAC,p,
PAC,p=2Re{mTp,m·AS,m*},
Tp,m=pnAR,nΨm*(x,y)·Ψn(x,y)dxdy.
PAC=2Re{T×AS*},
γ¯SR=|ES*(x,y,td)·ER(x,y)dxdy|2p|ES(x,y,td)|2dxdyp|ER(x,y)|2dxdyp,
SANR=[2Re{ES*(x,y,td)·ER(x,y)dxdy}]2p|ER(x,y)|2dxdyp·E/te,
SANR=2|ES*(x,y,td)·ER(x,y)dxdy|2p|ER(x,y)|2dxdyp·E/te=2γ¯SR2N¯S.
SANR=2N¯S(iλi2)teMN¯RE,
NSpeckle=[mean(pNAC,p2)std(pNAC,p2)]2=(iλi2)22iλi4.

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